基于提升小波变换的医学图像融合算法

图像融合是将多幅图像的信息综合到一幅图像的技术,它使得融合后的图像包含更为准确、更为全面可靠的图像描述。为了改善传统医学图像融合算法对细节信息的丢失,采用提升小波的方式将源医学图像进行分解,并分别对高低频采用不同的融合规则,最后经小波逆变换得到目标图像。仿真实验结果表明,该算法是有效可行的。     

电容层析成像技术中影响图像重建质量的因素分析

电容层析成像技术（ECT）作为一种多相流参数检测技术,具有快速、非侵入、结构简单、无辐射、成本低等特点,而图像重建质量和速度是阻碍电容层析成像技术工业应用的关键性问题,本文讨论了影响图像重建的因素,在采用线性反投影算法、正则化求逆算法以及迭代法的基础上,研究了单元划分数目、有限元形状、极板数以及介电常数四种因素对成像质量的影响．研究结果对获得最佳成像效果具有一定的指导意义．     

基于NSCT变换的红外与可见光图像融合方法

针对小波变换不能很好地表达图像边缘信息，NSCT变换对图像细节信息表达缺失的问题，本文提出了一种改进的基于NSCT变换的图像融合方法．首先将经过预处理和配准后的红外图像和可见光图像进行NSCT变换，得到各个源图像的低频和高频系数，然后对分解后的低频系数采用小波变换的融合规则进行融合处理，高频系数则采用基于特征的区域能量的融合规则进行融合处理，最后对融合后的系数进行NSCT反变换得到融合图像．仿真实验表明，采用改进的NSCT融合方法对红外与可见光图像的融合有良好的效果，图像更清晰，信息更全面．     

New Iris Localization Method Based on Chaos Genetic Algorithm

This paper present a new method based on Chaos Genetic Algorithm (CGA) to localize the human iris in a given image. First, the iris image is preprocessed to estimate the range of the iris localization, and then CGA is used to extract the boundary of the iris. Simulation results show that the proposed algorithms is efficient and robust, and can achieve sub pixel precision. Because Genetic Algorithms (GAs) can search in a large space, the algorithm does not need accurate estimation of iris center for subsequent localization, and hence can lower the requirement for original iris image processing. On this point, the present localization algirithm is superior to Daugman‘s algorithm.     

Infrared and visible image fusion based on region of interest detection and nonsubsampled contourlet transform

In order to enhance the contrast of the fused image and reduce the loss of fine details in the process of image fusion,a novel fusion algorithm of infrared and visible images is proposed.First of all,regions of interest(RoIs)are detected in two original images by using saliency map.Then,nonsubsampled contourlet transform(NSCT)on both the infrared image and the visible image is performed to get a low-frequency sub-band and a certain amount of high-frequency sub-bands.Subsequently,the coefcients of all sub-bands are classified into four categories based on the result of RoI detection:the region of interest in the low-frequency sub-band(LSRoI),the region of interest in the high-frequency sub-band(HSRoI),the region of non-interest in the low-frequency sub-band(LSNRoI)and the region of non-interest in the high-frequency sub-band(HSNRoI).Fusion rules are customized for each kind of coefcients and fused image is achieved by performing the inverse NSCT to the fused coefcients.Experimental results show that the fusion scheme proposed in this paper achieves better efect than the other fusion algorithms both in visual efect and quantitative metrics.     

IMAGE ANALYSIS BASED ON EDGE DETECTION TECHNIQUES

IntroductionEdges are pixels where brightness changesabruptly and often used in image analysis for find-ing region boundaries.It locates sharp changes inthe intensity function.Edges detection is basic im-age features.They carry useful information aboutobject boundaries.Edges can be used for object i-dentification,image analysis and image filteringapplications as well.We shall consider as an edgethe border between two homogeneous image re-gions having different illumination.This definitionimp…     

基于结构光的多投影显示系统图像对准算法

为了解决多投影显示系统的图像对准问题,提出了一种基于结构光投影技术的对准算法.该算法通过求取等相位线的交点来建立投影机图像与相机拍摄图像间的映射关系,对于投影机图像上任一像素点,有水平和垂直2个相位值.在相机图像的水平相位展开图中找出与该点水平相位值相等的离散坐标点的位置,拟合出一条水平等相位线,同理,可以得到它的一条垂直等相位线;求出水平和垂直等相位线的交点,即为该点对应于相机图像中的像素点.该算法无需知道显示墙的解析表达式和相机的内部参数,适用于任意光滑的曲面显示墙.对准后图像与原始图像的对比实验表明:峰值信噪比达到27.904,结构相似度为0.972 4,说明该算法能有效提高图像的对准精度.      

测量噪声相关情况下的航迹融合和测量融合

研究了测量噪声相关情况下的航迹融合和测量融合问题,根据线性无偏最小方差估计理论,推导了噪声相关情况下的多传感器跟踪系统的航迹融合和测量融合算法.经Monte Carlo仿真表明,文中给出的考虑噪声相关的航迹融合和测量融合算法的跟踪精度均高于相应的不考虑噪声相关的传统算法,且附加的计算量很小.     

Synthetically Evaluation System for Multi-source Image Fusion and Experimental Analysis

Introduction The image fusion technology produces a singleimage from a set of input images. The fused imageshould have more complete information which ismore useful for human or machine perception.With the merits of high degree of system explo-ration, automation, availability, reliability, capa-bility and low cost, it boasts broad application per-spective in many fields such as computer vision,automatic object detection, image processing, par-allel and distributed processing, robotics and re-m…     

基于数字图像技术的露石混凝土表面构造研究

运用数字图像技术实现了露石混凝土路面(EACCP)图像像素值量化计算,建立了露石表面像素差平均值与构造深度的关系模型;通过采集的数字图像计算分析了露石表面构造深度,评价了EACCP露石表面构造质量。实例分析表明:数字图像技术的露石表面构造检测方法,能方便快捷地进行露石路表构造深度检测,有利于实现测量工作的连续化。     

基于混沌系统的量子彩色图像加密算法

为了提高图像安全性,将混沌系统引入到量子图像加密领域. 首先通过Chen混沌将图像按位异或;然后将彩色图像表示为量子的叠加态,通过Logistic混沌序列产生幺正矩阵对量子图像进行置乱;再次产生一个混沌序列对每个像素的红绿蓝三基色进行随机互换,达到对量子图像加密的目的;最后,在经典计算机上进行了模拟实验,结果表明加密后图像直方图更为平滑,像素平均分布在0～255范围内,图像相邻像素相关性低,加密图像红绿蓝像素相关系数平均值分别为0.001 6、0.001 7和0.003 8,并且密钥敏感性高,能有效抵抗穷举攻击和统计攻击,算法具有良好的有效性和可行性.      

An Improvement of Russo's Fuzzy Noise-Filtering for Image Processing

We adapted Russo's image noise filtering technique by introducing an adaptive parameter, noise possibility. This parameter potentially indicates whether a pixel is noise. The improved Russo's method was applied to process the Lena image and a remote sensing image corrupted by noise. The results show that it has a stronger noise filtering ability than other traditional techniques such as Wiener filtering.     

基于最佳指数因子的自适应权值图像融合

依据现有的多波段遥感影像的融合方法和多波段图像融合效果的客观评价准则,提出了基于最佳指数因子的自适应权值图像融合算法.最后,结合互联网卫星数据,给出了实验结果.结果表明,该方法为研究人员提供一个较佳的融合后影像.     

IMAGE SEGMENTATION BASED ON MARKOV RANDOM FIELD AND WATERSHED TECHNIQUES

IntroductionThere are many methods to perform imagesegmentation and edge detection tasks that incor-porate region- growing and edge detection tech-niques,for example,it is applying edge detectiontechniques to obtain Difference In Strength( DIS)map then employ region growing techniques towork on the map as in Refs.[1 ,2 ]. In the others,combining both special and intensity information inimage segmentation approach based on multi- reso-lution edge detection,region selection and intensi-ty thre…     

基于结构性字典学习的高光谱遥感图像分类

为提高高光谱遥感图像的分类精度,提出了一种新的结构性稀疏表示及字典学习的高光谱遥感图像分类方法.该方法能同时利用高光谱遥感图像像素间的空间及光谱关系得到表示每个像素的字典,被划分为同一像素组的像素具有通用的稀疏模式;由字典计算图像的稀疏表示系数获得遥感图像的稀疏表示特征;利用线性支持向量机算法实现对高光谱遥感图像的分类.对AVIRIS和ROSIS高光谱遥感图像进行的实验结果表明:提出的方法比普通字典学习分类精度分别提高0.041 1和0.046 6,Kappa系数分别提高0.179 3和0.056 3.      

Fusion of remote sensing images based on nonsubsampled contourlet transform and region segmentation

The purpose of remote sensing images fusion is to produce a fused image that contains more clear, accurate and comprehensive information than any single image. A novel fusion method is proposed in this paper based on nonsubsampled contourlet transform (NSCT) and region segmentation. Firstly, the multispectral image is transformed to intensity-hue-saturation (IHS) system. Secondly, the panchromatic image and the component intensity of the multispectral image are decomposed by NSCT. Then the NSCT coefficients of high and low frequency subbands are fused by different rules, respectively. For the high frequency subbands, the fusion rules are also unalike in the smooth and edge regions. The two regions are segregated in the panchromatic image, and the segmentation is based on particle swarm optimization. Finally, the fusion image can be obtained by performing inverse NSCT and inverse IHS transform. The experimental results are evaluated by both subjective and objective criteria. It is shown that the proposed method can obtain superior results to others.     

字轮电能表读数系统的数字识别算法

提出了字轮电能表读数系统字轮区域图像定位、数字图像区域定位和数字区域图像信息增强3方面的算法,并对它们进行了适当的融合.经过试验表明,基于这些算法的数字识别结果准确率较高.     

基于MS-RG混合图像分割模型的道路检测研究

道路场景因其结构的多样性、纹理变化的复杂性和自然曝光的不稳定性,使得传统基于道路分割的道路检测方法大多存在信息冗余,并且存在边界丢失、模糊等质量问题.本文首先在道路图像上使用 Meanshift均值漂移算法,通过空间内的概率密度呈梯形上升去寻找局部最优,并搜索属于同一模点的像素然后生成获得超像素块.然后利用 Meanshift算法获得的聚类超像素块进行多种子点区域生长,规范生长规则,克服不能得到封闭边界的缺陷,改进道路图像的分割效果.实验结果表明,本文提出的模型适用性强,相比于传统方法有效地提升了分割准确性和实时性,可准确识别出图像中的道路信息,确保车辆能够行驶在可行驶区域上.     

Filter bank based nonlocal means for denoising magnetic resonance images

Image denoising is a classical problem in image processing. Its essential goal is to preserve the image features and to reduce noise effectively. The nonlocal means （NL-means） filter is a successful approach proposed in recent years due to its patch similarity comparison. However, the accuracy of similarities in this algorithm degrades when it suffers from heavy noise. In this paper, we introduce feature similarities based on a multi- channel filter into NL=means filter. The multi-bank based feature vectors of each pixel in the image are computed by convolving from various orientations and scales to Leung-Malik set （edge, bar and spot filters）, and then the similarities based on this information are computed instead of pixel intensity. Experiments are carried out with Rician noise. The results demonstrate the superior performance of the proposed method. The wavelet-based method and traditional NL-means in term of both mean square error （MSE） and perceptual quality are compared with the proposed method, and structural similarity （SSIM） and quality index based on local variance （QILV） are given.     

���ڸĽ�����ɫ������ֱ��ͼ���µ�Mean-Shift�㷨

为了提高复杂环境下智能视频监控对运动目标跟踪的可靠性,提出一种基于改进的颜色特征和直方图更新的Mean-Shift跟踪算法.该算法利用像素点局部颜色变化作为跟踪目标像素点特征,弥补单一颜色值特征对目标表征的不足;并根据Mean-Shift跟踪结果和目标匹配程度对目标直方图进行更新,保证在目标姿态和大小发生变化时目标特征直方图的有效性.实验结果表明：与传统Mean-Shift算法相比,改进的颜色特征减小了相似背景像素对运动目标的干扰,目标直方图的更新提高了Mean-Shift算法对目标姿态和大小改变的鲁棒性.算法提高了基于颜色特征的Mean-Shift算法对复杂环境中运动目标进行实时跟踪的可靠性.